4  A reanalysis

Razin et al’s model makes some obviously unrealistic assumptions, such as the assumption that benefit payments are the same for everyone. Razin et al (p911) also caution that their empirical results should be seen merely as ‘suggestive’ and ‘broadly consistent with the main implications of the theory’. They note (p915) that further statistical analysis is needed, such as the use of instrumental variables to deal with the possibility of reverse causation.

Both the unrealistic assumptions and the limited statistical testing are readily defensible. Razin et al’s work is an early exploration of a difficult topic. Moreover, much of the heuristic value of Razin et al’s model is due to its simplicity, which inevitably requires the sacrifice of some realism. Little is therefore gained from merely pointing out counter-examples to the assumptions or potential limitations in the statistical analysis. What is useful, however, is the identification of areas where substantively important extensions can be added to model without unduly complicating it. That is the aim of this section.

Razin et al’s theoretical model and statistical analysis both recognize only one sort of dependant. A straightforward extension of Razin et al’s framework suggests, however, that the effect on equilibrium taxes and benefits of increasing the number of young dependants may well be different from the effect of increasing the number of old dependants. The exact effects depend on whether benefit payments to children are treated as if they were payments to the children’s parents.

The analysis is simpler when benefit payments are treated as if they were not payments to the parents. In this case, a rise in the number of young dependants parallels a rise in the number of old dependants, in that it unambiguously increases the extent of the ‘fiscal leakage’ and discouragement of education. However, because young people, unlike old people, cannot vote, a rise in their number adds no one to the pro-tax coalition. In sum, a rise in youth dependency, unlike a rise in old age dependency, does not have a voting power effect to offset the fiscal leakage and education effects. Youth dependency, unlike old age dependency, is unambiguously predicted to be negatively correlated with benefit levels.

The analysis is different, however, if some or all of the benefits paid to children are treated as if they were paid to the children’s parents. In this case, working age parents see the tax and transfer system as having less fiscal leakage than do working age non-parents. A rise in the number of young dependants may add to or subtract from the pro-tax coalition, depending on how childbearing and innate ability are distributed among the working age population. Without knowledge of these distributions, the framework cannot be used to make unconditional predictions about whether youth dependency will be negatively or positively correlated with benefits levels.

The remainder of this section examines the empirical evidence. The first step is to disaggregate Razin et al’s original dependency ratio (defined as one minus the labour force participation rate). Equation 1 shows one way of doing so. This decomposition ignores labour force participation by people aged 65 and over; the rationale for doing so is that participation rates at these ages are typically under 10%, and treating them as zero simplifies the analysis to follow. To maintain comparability with Razin et al’s original analysis, the decomposition includes working age people not in the labour force, though the main focus is on old and young dependants. The numbers in brackets underneath Equation 1 are the means during the period 1965-1992 across the 13 countries included in Razin et al’s original regression. As is apparent, the third term on the right, representing old-age dependency, makes up less than one quarter of the combined dependency ratio.

(1)

As Table 2 shows, the old-age dependency ratio is negatively correlated with the combined ratio over the period 1965-1992. The combined dependency ratio did, as Razin et al point out, fall between 1965 and 1992. The old-age dependency ratio, however, rose.

Table 3 shows the results of repeating Razin et al’s (2002: Table 1) original fixed effects panel regression, replacing the combined dependency ratio with three separate dependency measures. For Specifications (3) and (6), which required more observations for growth in GDP per capita than were available in Razin et al’s dataset, growth rates were calculated from the Laspeyres Index GDP per capita series in the Penn World Tables (Heston, Summers and Aten 2002). Specifications (1), (2), (4), and (5) cover 1965-1992, the same period as used by Razin et al. Specification (3) covers the period 1965-1996, and Specification (6), 1960-1996. For all periods, some countries have missing observation, so the panel is unbalanced.

Source - Calculated from data supplied by Razin et al and data from the OECD labour statistics online database.

At first sight, an attractive way of disaggregating the combined dependency ratio is to use the three age-specific measures set out in Equation 1. This is what Specifications (1) and (4) in Table 3 do. Interpretation of Specifications (1) and (4) is, however, made difficult by the presence of the term for working-age dependency. This term is the product of two different things: the proportion of the 15-64 age group not in the labour force, and the proportion of the total population in the 15-64 age group. Moreover, the proportion in the 15-64 age group is perfectly (negatively) correlated with sum of the youth and old-age dependency ratios.

Specifications (2) and (5) replace the working-age dependency term with the labour force participation rate. The terms capturing dependency now all have clear interpretations. The term for the proportion of the population aged 0-14 shows the effect of holding both labour force participation and the proportion aged 65 and over constant, and increasing the proportion of the population aged 0-14 at the expense of the proportion aged 15-64. The term for the proportion aged 65 and over has an analogous interpretation. The term for labour force participation shows the effect of increasing participation while holding age structure constant. Specifications (3) and (6) are identical to Specifications (2) and (5), except that longer time periods have been used.

*Shorter periods are used for countries with missing data.

Notes – All specifications include fixed effects (coefficients not shown). Values for R² do not include the contribution of the fixed effects (these values were calculated by subtracting country-specific means from all dependent and independent variables before conducting the analysis). The numbers in brackets are t-statistics.

The results for Specifications (2) and (3) show that, all else equal, higher population shares for ages 0-14 at the expense of ages 15-64 are associated with lower levels of taxes on labour income. Conversely, higher population shares for ages 65 and over are associated with higher taxes. Neither of these results is sensitive to the choice of period. The results for Specifications (5) and (6) show that higher population shares for ages 0-14 are associated with reductions in benefits per capita. The relationship between old-age dependency and benefits per capita is unclear. If the period 1965-1992 is used, the relationship is positive but not statistically significant at the 5% level; if the period 1960-1996 is used, the relationship is positive and statistically significant. The overall finding is that more young people implies lower taxes and lower benefits, while more old people implies higher taxes and, possibly, higher benefits.

Specifications (2) and (3) show that, holding age structure constant, higher labour force participation is associated with lower taxes. This result should be treated with caution, however, as there is likely to be reverse causality from taxes to participation. No clear relationship between benefit levels and labour force participation is apparent from Specifications (5) and (6).